Dena DeMarco

500 total citations · 1 hit paper
13 papers, 344 citations indexed

About

Dena DeMarco is a scholar working on Oncology, Radiology, Nuclear Medicine and Imaging and Molecular Biology. According to data from OpenAlex, Dena DeMarco has authored 13 papers receiving a total of 344 indexed citations (citations by other indexed papers that have themselves been cited), including 12 papers in Oncology, 6 papers in Radiology, Nuclear Medicine and Imaging and 4 papers in Molecular Biology. Recurrent topics in Dena DeMarco's work include CAR-T cell therapy research (9 papers), Monoclonal and Polyclonal Antibodies Research (5 papers) and Multiple Myeloma Research and Treatments (4 papers). Dena DeMarco is often cited by papers focused on CAR-T cell therapy research (9 papers), Monoclonal and Polyclonal Antibodies Research (5 papers) and Multiple Myeloma Research and Treatments (4 papers). Dena DeMarco collaborates with scholars based in United States, Netherlands and Denmark. Dena DeMarco's co-authors include Roberto S Oliveri, Brian Elliott, Kim Linton, Martin Hutchings, Michael Roost Clausen, Martine E.D. Chamuleau, Pieternella J. Lugtenburg, Rogier Mous, Peter Johnson and Anna Sureda and has published in prestigious journals such as The Lancet, Journal of Clinical Oncology and Blood.

In The Last Decade

Dena DeMarco

12 papers receiving 340 citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Dose escalation of subcutaneous epcoritamab in patients with relapsed or refractory B-cell non-Hodgkin lymphoma: an open-label, phase 1/2 study

2021 212 citations Martin Hutchings, Rogier Mous et al. The Lancet profile →

Peers

Dena DeMarco

ONCOL

PFM

RNMI

IMMUN

GENET

Keith Fay Australia

Marie-Elisabeth Goebeler Germany

Yajuan Qin United States

Linda Lundberg Switzerland

James Relf Switzerland

Cyrus Khan United States

Horst Hummel Germany

Sandrine Payrard France

Michelle Poon Singapore

Rodica Morariu-Zamfir United States

Keith Fay Australia

Dena DeMarco

230 ×0.8

ONCOL

162 ×0.7

PFM

93 ×1.0

RNMI

70 ×0.9

IMMUN

40 ×0.5

GENET

Citations per year, relative to Dena DeMarco Dena DeMarco (= 1×) peers Keith Fay

Countries citing papers authored by Dena DeMarco

Since Specialization

Citations

This map shows the geographic impact of Dena DeMarco's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Dena DeMarco with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Dena DeMarco more than expected).

Fields of papers citing papers by Dena DeMarco

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Dena DeMarco. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Dena DeMarco. The network helps show where Dena DeMarco may publish in the future.

Co-authorship network of co-authors of Dena DeMarco

This figure shows the co-authorship network connecting the top 25 collaborators of Dena DeMarco. A scholar is included among the top collaborators of Dena DeMarco based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Dena DeMarco. Dena DeMarco is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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13 of 13 papers shown

Li, Tommy, Ida H. Hiemstra, Christopher Chiu, et al.. (2022). Semimechanistic Physiologically‐Based Pharmacokinetic/Pharmacodynamic Model Informing Epcoritamab Dose Selection for Patients With B‐Cell Lymphomas. Clinical Pharmacology & Therapeutics. 112(5). 1108–1119. 25 indexed citations

Hutchings, Martin, Rogier Mous, Michael Roost Clausen, et al.. (2021). Dose escalation of subcutaneous epcoritamab in patients with relapsed or refractory B-cell non-Hodgkin lymphoma: an open-label, phase 1/2 study. The Lancet. 398(10306). 1157–1169. 212 indexed citations breakdown →

Hutchings, Martin, Rogier Mous, Michael Roost Clausen, et al.. (2021). SUBCUTANEOUS EPCORITAMAB IN PATIENTS WITH RELAPSED/REFRACTORY B‐CELL NON‐HODGKIN LYMPHOMA: SAFETY PROFILE AND ANTI‐TUMOR ACTIVITY. Hematological Oncology. 39(S2). 1 indexed citations

Clausen, Michael Roost, Pieternella J. Lugtenburg, Martin Hutchings, et al.. (2021). Subcutaneous epcoritamab in patients with relapsed/refractory B-cell non-Hodgkin lymphoma: Safety profile and antitumor activity.. Journal of Clinical Oncology. 39(15_suppl). 7518–7518. 14 indexed citations

Hutchings, Martin, Pieternella J. Lugtenburg, Rogier Mous, et al.. (2020). Epcoritamab (GEN3013; DuoBody-CD3×CD20) to induce complete response in patients with relapsed/refractory B-cell non-Hodgkin lymphoma (B-NHL): Complete dose escalation data and efficacy results from a phase I/II trial.. Journal of Clinical Oncology. 38(15_suppl). 8009–8009. 19 indexed citations

Hutchings, Martin, Pieternella J. Lugtenburg, Rogier Mous, et al.. (2020). ABCL-346: Subcutaneous (SC) Epcoritamab (GEN3013; DuoBody-CD3×CD20) in Patients with Relapsed/Refractory (R/R) B-Cell Non-Hodgkin Lymphoma (B-NHL): Dose-Escalation Data from a Phase I/II Trial. Clinical Lymphoma Myeloma & Leukemia. 20. S274–S274.

Li, Tommy, Ida H. Hiemstra, Roberto S Oliveri, et al.. (2020). Novel Semi-Mechanistic Model Leveraging Preclinical and Clinical Data to Inform the Recommended Phase 2 Dose (RP2D) Selection for Epcoritamab (DuoBody CD3xCD20). Blood. 136(Supplement 1). 35–36. 4 indexed citations

Hutchings, Martin, Rogier Mous, Michael Roost Clausen, et al.. (2020). Subcutaneous Epcoritamab Induces Complete Responses with an Encouraging Safety Profile across Relapsed/Refractory B-Cell Non-Hodgkin Lymphoma Subtypes, Including Patients with Prior CAR-T Therapy: Updated Dose Escalation Data. Blood. 136(Supplement 1). 45–46. 42 indexed citations

Lugtenburg, Pieternella J., Rogier Mous, Michael Roost Clausen, et al.. (2019). First-in-Human, Phase 1/2 Trial to Assess the Safety and Clinical Activity of Subcutaneous GEN3013 (DuoBody®-CD3×CD20) in B-Cell Non-Hodgkin Lymphomas. Blood. 134(Supplement_1). 758–758. 16 indexed citations

10.

Du, Xin, Jie Jin, Zhen Cai, et al.. (2016). Long-term use of lenalidomide and low-dose dexamethasone in Chinese patients with relapsed/refractory multiple myeloma: MM-024 Extended Access Program. BMC Cancer. 16(1). 46–46. 1 indexed citations

11.

Huang, Shang‐Yi, Yuan-Bin Yu, Su‐Peng Yeh, et al.. (2016). A noninterventional observational registry of patients with multiple myeloma treated with lenalidomide in Taiwan. Journal of the Formosan Medical Association. 116(9). 705–710. 2 indexed citations

12.

Yu, Li, Xin Du, Jie Jin, et al.. (2015). Lenalidomide plus low-dose dexamethasone in Chinese patients with relapsed or refractory multiple myeloma and renal impairment. International Journal of Hematology. 101(6). 569–577. 7 indexed citations

13.

Huang, Shang‐Yi, Yao Yu, W Y Kao, et al.. (2015). A Non-interventional Observational Registry of Patients (Pts) With Relapsed/Refractory Multiple Myeloma (RRMM) Treated With Lenalidomide (LEN) and Dexamethasone (DEX) in Taiwan. Clinical Lymphoma Myeloma & Leukemia. 15. e299–e299. 1 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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